Author name cluster

Bin Du

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers

2 author rows

IROS Conference 2022 Conference Paper

Flexible Collision-free Platooning Method for Unmanned Surface Vehicle with Experimental Validations

Bin Du
Bin Lin
Wei Xie 0009
Weidong Zhang 0004
Rudy R. Negenborn
Yusong Pang

This paper addresses the flexible formation problem for unmanned surface vehicles in the presence of obstacles. Building upon the leader-follower formation scheme, a hybrid line-of-sight based flexible platooning method is proposed for follower vehicle to keep tracking the leader ship. A fusion artificial potential field collision avoidance approach is tailored to generate optimal collision-free trajectories for the vehicle to track. To steer the vehicle towards and stay within the neighborhood of the generated collision-free trajectory, a nonlinear model predictive controller is designed. Experimental results are presented to validate the efficiency of proposed method, showing that the unmanned surface vehicle is able to track the leader ship without colliding with the surrounded static obstacles in the considered experiments.

Details

ICRA Conference 2021 Conference Paper

Multi-Robot Dynamical Source Seeking in Unknown Environments

Bin Du
Kun Qian 0018
Hassan Iqbal
Christian G. Claudel
Dengfeng Sun

This paper presents an algorithmic framework for the distributed on-line source seeking, termed as DoSS, with a multi-robot system in an unknown dynamical environment. Our algorithm, building on a novel concept called dummy confidence upper bound (D-UCB), integrates both estimation of the unknown environment and task planning for the multiple robots simultaneously, and as a result, drives the team of robots to a steady state in which multiple sources of interest are located. Unlike the standard UCB algorithm in the context of multi-armed bandits, the introduction of D-UCB significantly reduces the computational complexity in solving subproblems of the multi-robot task planning. This also enables our DoSS algorithm to be implementable in a distributed on-line manner. The performance of the algorithm is theoretically guaranteed by showing a sub-linear upper bound of the cumulative regret. Numerical results on a real-world methane emission seeking problem are also provided to demonstrate the effectiveness of the proposed algorithm.

Details

EAAI Journal 2021 Journal Article

The object-oriented dynamic task assignment for unmanned surface vessels

Bin Du
Yu Lu
Xiaotong Cheng
Weidong Zhang
Xuesong Zou

This paper investigates the task assignment and guidance issues of unmanned surface vessels (USVs) interception. When the USVs formation is invaded by some moving objects during its escort, it is necessary for the unmanned systems to assign defenders to prevent attackers approaching the vulnerable target in antagonistic scenarios. This action requires efficient guidance and task assignment strategies. With this in mind, this paper presents the Integral Proportional Navigation Guidance (IPNG) with Tabu Dynamic Consensus-Based Auction Algorithm (TDCBAA) in marine interception scenario. First, IPNG is introduced in the interception game considering the USV kinematic model, which can effectively reduce the individual interception time. Second, a new bidding function is designed for moving objects interception with the consideration of the attackers’ types, positions and interception time. Finally, a TDCBAA is designed to solve the task assignment subproblem, resulting in a shorter overall interception time and a higher interception success rate. Simulations demonstrate that the proposed algorithm can optimize the allocation of defenders in real-time and intercept the attackers more quickly compared with other classical algorithms, which is more suitable in situations where attackers are approaching from all directions.

Details DOI